J. Manuf. Mater. Process., Volume 8, Issue 3 (June 2024) – 30 articles

Humping is a common defect in direct energy deposition processes that reduces the geometric integrity of printed products. The available literature on humping detection is deemed reactive, as they focus on detecting late-stage melt pool spatial abnormalities. Therefore, this work introduces a novel, proactive indicator designed to detect early-stage spatiotemporal abnormalities. Specifically, the proposed indicator monitors the variability of instantaneous melt pool solidification-front speed (VIMPS). The solidification front dynamics quantify the intensity of cyclic melt pool elongation induced by early-stage humping. VIMPS tracks the solidification front dynamics based on the variance in the melt pool infrared radiations. Qualitative and quantitive analysis of the collected infrared data confirms VIMPS’s utility in reflecting the intricate humping-induced dynamics and defects. Experimental results proved VIMPS’ proactivity. By capturing early spatiotemporal abnormalities, VIMPS predicted humping by up to 10 s before any significant geometric defects. In contrast, current spatial abnormality-based methods failed to detect humping until 20 s after significant geometric defects had occurred. VIMPS’ proactive detection capabilities enable effective direct energy deposition control, boosting the process’s productivity and quality. Full article

Being a difficult-to-cut material, Fiber Metal Laminates (FML) often pose challenges during conventional drilling and require judicious selection of machining parameters to ensure defect-free laminates that can serve reliably during their service lifetime. Helical milling is a promising technique for producing good-quality holes and is preferred over conventional drilling. The paper compares conventional drilling with the helical milling technique for producing holes in carbon fiber-reinforced aluminum laminates. The effect of machining parameters, such as cutting speed and axial feed, on the magnitude of cutting force and the machining temperature during conventional drilling as well as helical milling is studied. It was observed that the thrust force produced during machining reduces considerably during helical milling in comparison to conventional drilling at a constant axial feed rate. The highest machining temperature recorded for helical milling was much lower in comparison to the highest machining temperature measured during conventional drilling. The machining temperatures recorded during helical milling were well below the glass transition temperature of the epoxy used in carbon fiber prepreg, hence protecting the prepreg from thermal degradation during the hole-making process. The surface roughness of the holes produced by both techniques is measured, and the surface morphology of the drilled holes is analyzed using a scanning electron microscope. The surface roughness of the helical-milled holes was lower than that for holes produced by conventional drilling. Scanning electron microscope images provided insights into the interaction of the hole surface with the chips during the chip evacuation stage under different speeds and feed rates. The microhardness of the aluminum layers increased after processing holes using drilling and helical milling operations. The axial feed/axial pitch had minimal influence on the microhardness increase in comparison to the cutting speed. Full article

Achieving a homogeneous and uniform powder bed surface as well as a defined, uniform layer thickness is crucial for achieving reproducible component properties that meet requirements when powder bed fusion of metals with a laser beam. The existing recoating processes cause wear of the recoater blade due to protruded, melted obstacles, which affects the powder bed surface quality locally. Impairments to the powder bed surface quality have a negative effect on the resulting component properties such as surface quality and relative density. This can lead either to scrapped components or to additional work steps such as surface reworking. In this work, an electric smoother is presented with which a wear-free and contactless smoothing of the powder bed can be realized. The achievable powder bed surface quality was analyzed using optical profilometry. It was found that the electric smoother can compensate for impairments in the powder bed surface and achieve a reproducible surface quality of the powder bed regardless of the initial extent of the impairments. Consequently, the electric smoother offers a promising opportunity to reduce the scrap rate in PBF-LB/M and to increase component quality. Full article

The foundry industry is responsible for the production of several potentially polluting and hazardous compounds. One of the major sources of pollution is the use of organic binders for the manufacturing of sand cores and sand moulds. To address this problem, in recent years, the use of low-emission products, known as inorganic binders, has been proposed. Their use in ferrous foundries, otherwise, is limited due to some problematic features that complicate their introduction in the manufacturing process, as often happens when a breakthrough innovation is introduced. In light of this, the aim of this work is to provide a Green Innovation Practice (GIP) to manage the introduction of green breakthrough innovations, as previously described, within an existing productive context. This practice was applied to better manage the experimental phase of the Green Casting Life Project, which aims to evaluate the possibility of using inorganic binders for the production of ferrous castings. After describing the state of the art of GIPs and their application in manufacturing contexts, the paper described the proposed GIP and its application to a real case consisting of testing inorganic binders in a ferrous foundry. Full article

In this study, the welding thermal cycle, as well as the microstructural and mechanical properties of welded AA6061-T6 plates, were studied. The plates were prepared and bead-on-plate welded using gas metal arc welding (GMAW). Numerical simulations using SYSWELD^® were performed to obtain the thermal distribution in the welded plates. The numerical heat source was calibrated using the temperatures obtained from the experimental work and the geometry of the melting pool. The mechanical properties were obtained through microhardness tests and were correlated with the welding thermal cycle. Moreover, the mechanical behavior and local deformation in the heat-affected zone (HAZ) were investigated using micro-flat tensile (MFT) tests with digital image correlation (DIC). The mechanical properties of the subzones in the HAZ were then correlated with the welding thermal cycle and with the microstructure of the HAZ. It was observed that the welding thermal cycle produced microstructural variations across the HAZ, which significantly affected the mechanical behavior of the HAZ subzones. The results revealed that MFT tests with the DIC technique are an excellent tool for studying the local mechanical behavior change in AA6061-T6 welded parts due to the welding heat. Full article

This paper describes a sample partitioning approach to retain or reject samples from an initial distribution of stability maps using milling test results. The stability maps are calculated using distributions of uncertain modal parameters that represent the tool tip frequency response functions and cutting force model coefficients. Test points for sample partitioning are selected using either (1) the combination of spindle speed and mean axial depth from the available samples that provides the high material removal rate, or (2) a spindle speed based on the chatter frequency and mean axial depth at that spindle speed. The latter is selected when an unstable (chatter) result is obtained from a test. Because the stability model input parameters are also partitioned using the test results, their uncertainty is reduced using a limited number of tests and the milling stability model accuracy is increased. A case study is provided to evaluate the algorithm. Full article

In order to avoid catastrophic events that degrade the quality of machined products, such as tool breakage, it is vital to have a prognostic system for monitoring tool wear during the micro-milling process. Despite the long history of the tool wear monitoring field, creating such a system to track, monitor, and foresee the rapid progression of tool wear still needs to be improved in the application of micro-milling. On the other hand, digital twin technology has recently become widely recognized as significant in manufacturing and, notably, within the Industry 4.0 ecosystem. Digital twin technology is considered a potential breakthrough in developing a prognostic tool wear monitoring system, as it enables the tracking, monitoring, and prediction of the dynamics of a twinned object, e.g., a CNC machine tool. However, few works have explored the digital twin technology for tool wear monitoring, particularly in the micro-milling field. This paper presents a novel tool wear monitoring system for micro-milling machining based on digital twin technology and an extended Kalman filter framework. The proposed system provides wear progression notifications to assist the user in making decisions related to the machining process. In an evaluation using four machining datasets of slot micro-milling, the proposed system achieved a maximum error mean of 0.038 mm from the actual wear value. The proposed system brings a promising opportunity to widen the utilization of digital twin technology with the extended Kalman filter framework for seamless data integration for wear monitoring service. Full article

Cutting simulations via the Finite Element Method (FEM) have recently gained more significance due to ever increasing computational performance and thus better resulting accuracy. However, these simulations are still time consuming and therefore cannot be deployed for an in situ evaluation of the machining processes in an industrial environment. This is due to the high non-linear nature of FEM simulations of machining processes, which require considerable computational resources. On the other hand, machine learning methods are known to capture complex non-linear behaviors. One of the most widely applied material models in cutting simulations is the Johnson–Cook material model, which has a great influence on the output of the cutting simulations and contributes to the non-linear behavior of the models, but its influence on cutting forces is sometimes difficult to assess beforehand. Therefore, this research aims to capture the highly non-linear behavior of the material model by using a dataset of multiple short-duration cutting simulations from Abaqus to learn the relationship of the Johnson–Cook material model parameters and the resulting cutting forces for a constant set of cutting conditions. The goal is to shorten the time to simulate cutting forces by encapsulating complex cutting conditions in dependence of material parameters in a single model. A total of five different models are trained and the performance is evaluated. The results show that Gradient Boosted Machines capture the influence of varying material model parameters the best and enable good predictions of cutting forces as well as deliver insights into the relevance of the material parameters for the cutting and thrust forces in orthogonal cutting. Full article

The influence of 3D printing parameters on compressive properties is an important factor in the application of additive manufacturing processes for products subjected to compressive loads in use. In this study, the compressive strength and compressive modulus of acrylonitrile/butadiene/styrene (ABS) test specimens fabricated using the fused deposition modeling (FDM) process were investigated with the aim of producing products of high-heeled shoes for women. The experimental part of the study includes a central composite experimental design to optimize the main 3D printing parameters (layer thickness, infill density, and extrusion temperature) and the infill geometry (honeycomb and linear at a 45° angle—L45) to achieve maximum printing properties of the 3D-printed products. The results show that the infill density has the greatest influence on the printing properties, followed by the layer thickness and, finally, the extrusion temperature as the least influential factor. The linear infill at a 45° angle resulted in higher compressive strength and lower compressive modulus values compared to the honeycomb infill. By optimizing the results, the maximum compressive strength (that of L45 is 41 N/mm² and that of honeycomb 35 N/mm²) and modulus (that of L45 is 918 N/mm² and that of honeycomb is 868 N/mm²) for both types of infill is obtained at a layer thickness of 0.1 mm and infill density of 40%, while the temperature for L45 can be in the range of 209 °C to 254 °C, but for the honeycomb infill, the processing temperature is 255 °C. Additionally, the study highlights the potential for sustainable manufacturing practices and the integration of advanced 3D printing technologies to enhance the efficiency and eco-friendliness of the production process. Full article

Incremental sheet forming represents a relatively recent technology, similar to the layered manufacturing principle of the rapid prototype approach; it is very suitable for small series production and guarantees cost-effectiveness because it does not require dedicated equipment. Research has initially shown that this process is effective in metal materials capable of withstanding plastic deformation but, in recent years, the interest in this technique has been increasing for the manufacture of complex polymer sheet components as an alternative to the conventional technologies, based on heating–shaping–cooling manufacturing routes. Conversely, incrementally formed polymer sheets can suffer from some peculiar defects, like, for example, twisting. To reduce the risk of this phenomenon, the occurrence of failures and poor surface quality, a viable way is to choose toolpath strategies that make the tool/sheet contact conditions less severe; this represents one of the main goals of the present research. Polycarbonate sheets were worked using incremental forming; in detail, cone frusta with a fixed-wall angle were manufactured with different toolpaths based on a reference and a stair strategy, in lubricated and dry conditions. The forming forces, the forming time, the twist angle, and the mean roughness were monitored. The analysis of the results highlighted that a stair toolpath involving an alternation of diagonal up and vertical down steps represents a useful strategy to mitigate the occurrence of the twisting phenomenon in incremental formed thermoplastic sheets and a viable way of improving the process towards a green manufacturing process. Full article

The multi-scale study of rock properties is a necessary step in the planning of oil and gas reservoir developments. The amount of core samples available for research is usually limited, and some of the samples can be distracted. The investigation of core reconstruction possibilities is an important task. An approach to the real-size reconstruction of porous media with a given (target) porosity and permeability by controlling the parameters of FFF 3D printing using CT images of the original core is proposed. Real-size synthetic core specimens based on CT images were manufactured using FFF 3D printing. The possibility of reconstructing the reservoir properties of a sandstone core sample was proven. The results of gas porometry measurements showed that the porosity of specimens No.32 and No.46 was 13.5% and 12.8%, and the permeability was 442.3 mD and 337.8 mD, respectively. The porosity of the original core was 14% and permeability was 271 mD. It was found that changing the layer height and nozzle diameter, as well as the retract and restart distances, has a direct effect on the porosity and permeability of synthetic specimens. This study shows that porosity and permeability of synthetic specimens depend on the flow of the material and the percentage of overlap between the infill and the outer wall. Full article

Electron beam–powder bed fusion (PBF-EB) is an additive manufacturing process that utilizes an electron beam as the heat source to enable material fusion. However, the use of a charge-carrying heat source can sometimes result in sudden powder explosions, usually referred to as “Smoke”, which can lead to process instability or termination. This experimental study investigated the initiation and propagation of Smoke using in situ high-speed synchrotron radiography. The results reveal two key mechanisms for Smoke evolution. In the first step, the beam–powder bed interaction creates electrically isolated particles in the atmosphere. Subsequently, these isolated particles get charged either by direct irradiation by the beam or indirectly by back-scattered electrons. These particles are accelerated by electric repulsion, and new particles in the atmosphere are produced when they impinge on the powder bed. This is the onset of the avalanche process known as Smoke. Based on this understanding, the dependence of Smoke on process parameters such as beam returning time, beam diameter, etc., can be rationalized. Full article

In traditional injection molding, each level of the process has its own monitoring and improvement initiatives. But in the upcoming industrial revolution, it is important to establish connections and communication among all stages, as changes in one stage might have an impact on others. To address this issue, digital twins (DTs) are introduced as virtual models that replicate the entire injection molding process. This paper focuses on the data and technology needed to build a DT model for injection molding. Each stage can have its own DT, which are integrated into a comprehensive model of the process. DTs enable the smart automation of production processes and data collection, reducing manual efforts in supervising and controlling production systems. However, implementing DTs is challenging and requires effort for conception and integration with the represented systems. To mitigate this, the current work presents a model for systematic knowledge-based engineering for the DTs of injection molding. This model includes fault detection systems, 3D printing, and system integration to automate development activities. Based on knowledge engineering, data analysis, and data mapping, the proposed DT model allows fault detection, prognostic maintenance, and predictive manufacturing. Full article

Powder deposition is a very important aspect of PBF-based additive manufacturing processes. Discrete Element Method (DEM) is commonly utilized by researchers to examine the physically complex aspects of powder-spreading methods. This work focuses on vibration-assisted doctor blade powder recoating. The aim of this work is to use experiment-verified DEM simulations in combination with Taguchi Design of Experiments (DoE) to identify optimum spreading parameters based on robust layer quality criteria. The verification of the used powder model is performed via angle of repose and angle of avalanche simulation–experiment cross-checking. Then, four criteria, namely layer thickness deviation, surface coverage ratio, surface root-mean-square roughness and true packing density, are defined. It has been proven that the doctor blade’s translational speed plays the most important role in defining the quality of the deposited layer. The true packing density was found to be unaffected by the spreading parameters. The vertical vibration of the doctor blade recoater was found to have a beneficial effect on the quality of the deposited layer. Ultimately, a weighted mean quality criteria analysis is mapped out. Skewness and kurtosis were proven to function as effective indicators of layer quality, showing a linear relation to the weighted means of the defined quality criteria. The specific weights that optimize this linearity were identified. Full article

Knowing the tolerance interval capabilities (TICs) of a manufacturing process is of prime interest, especially if specifications link the manufacturer to a customer. These TICs can be determined using the machine performance concept of ISO 22514. However, few works have applied this to Additive Manufacturing printers, while testing most of the printing area as recommended takes a very long time (nearly 1 month is common). This paper, by proposing a novel part design called COMPAQT (Component for Machine Performances Assessment in Quick Time), aims at giving the same level of printing area coverage, while keeping the manufacturing time below 24 h. The method was successfully tested on a material extrusion printer. It allowed the determination of potential and real machine tolerance interval capabilities. Independently of the feature size, those aligned with the X axis achieved lower TICs than those aligned with the Y axis, while the Z axis exhibited the best performance. The measurements specific to one part exhibited a systematic error centered around 0 mm ± 0.050 mm, while those involving two parts reached up to 0.314 mm of deviation. COMPAQT can be used in two applications: evaluating printer tolerance interval capabilities and tracking its long-term performance by incorporating it into batches of other parts. Full article

Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess several trajectory strategies, such as contour, zigzag, raster, and even space-filling, to search for the best strategy according to the case. However, handling complex geometries by this means poses computational efficiency concerns. This research aimed to explore the potential of machine learning techniques as a solution to increase the computational efficiency of such algorithms. First, reinforcement learning (RL) concepts are introduced and compared with supervised machining learning concepts. The Multi-Armed Bandit (MAB) problem is explained and justified as a choice within the RL techniques. As a case study, a space-filling strategy was chosen to have this machining learning optimisation artifice in its algorithm for GMA-AM printing. Computational and experimental validations were conducted, demonstrating that adding MAB in the algorithm helped to achieve shorter trajectories, using fewer iterations than the original algorithm, potentially reducing printing time. These findings position the RL techniques, particularly MAB, as a promising machining learning solution to address setbacks in the space-filling strategy applied. Full article

Optimizing process parameters to minimize defects remains an important challenge in injection molding (IM). Machine learning (ML) techniques offer promise in this regard, but their application often requires extensive datasets. Transfer learning (TL) emerges as a solution to this problem, leveraging knowledge from related tasks to enhance model training and performance. This study explores TL’s viability in predicting weld line visibility in injection-molded components using artificial neural networks (ANNs). TL techniques are employed to transfer knowledge between datasets related to different components. Furthermore, both source datasets obtained from simulations and experimental tests are used during the study. In order to use process simulations to obtain data regarding the presence of surface defects, it was necessary to correlate an output variable of the simulations with the experimental observations. The results demonstrate TL’s efficacy in reducing the data required for training predictive models, with simulations proving to be a cost-effective alternative to experimental data. TL from simulations achieves comparable predictive metric values to those of the non-pre-trained network, but with an 83% reduction in the required data for the target dataset. Overall, transfer learning shows promise in streamlining injection molding optimization and reducing manufacturing costs. Full article

Magnetic pulse welding (MPW) employs a strong pulsed magnetic field to accelerate parts against each other, thus forming an impact joint. Single-turn tool coils and field-shapers (FSs) used in MPW operate under the most demanding conditions, such as magnetic fields of 40–50 T with periods lasting tens of microseconds. With the use of conventional copper and bronze coils, intense thermo-mechanical stresses lead to the rapid degradation of the working bore. This work aimed to improve the efficiency of field-shapers and focused on the development of two- and four-slit FSs with a nanocomposite Cu 18Nb brazed wire acting as an inner current-carrying layer. The measured ratios of the magnetic field to the discharge current were 56.3 and 50.6 T/MA for the two- and four-slit FSs, respectively. FEM calculations of the magnetic field generated showed variations of 6–9% and 3% for the two- and four-slit FSs, respectively. The ovality percentages following copper tube compression were 27% and 7% for the two- and four-slit FSs, respectively. The measured deviations in the weld-joining length were 11% and 1.4% in the two- and four-slit FSs, respectively. Compared to the previous experiments on an entirely steel inductor, the novel FS showed significantly better results in terms of its efficiency and the homogeneity of its magnetic field. Full article

Dissimilar welds between ferritic and austenitic steels represent a good solution for exploiting the best performance of stainless steels at high and low temperatures and in aggressive environments, while minimizing costs. Therefore, they are widely used in nuclear and petrochemical plants; however, due to the different properties of the steels involved, the welding process can be challenging. Fusion welding can be specifically applied to connect low-carbon or low-alloy steels with high-alloy steels, which have similar melting points. The welding of thick plates can be performed with an electric arc in multiple passes or in a single pass by means of laser beam equipment. Since the microstructure and, consequently, the mechanical properties of the weld are closely related to the composition, the choice of the filler metal and processing parameters, which in turn affect the dilution rate, plays a fundamental role. Numerous technical solutions have been proposed for welding dissimilar steels and much research has developed on welding metallurgy; therefore, this article is aimed at a review of the most recent scientific literature on issues relating to the fusion welding of ferritic/austenitic steels. Two specific sections are dedicated, respectively, to electric arc and laser beam welding; finally, metallurgical issues, related to dilution and thermal field are debated in the discussion section. Full article

This critical review provides a comprehensive analysis of various condition monitoring techniques pivotal in additive manufacturing (AM) processes. The reliability and quality of AM components are contingent upon the precise control of numerous parameters and the timely detection of potential defects, such as lamination, cracks, and porosity. This paper emphasizes the significance of in situ monitoring systems—optical, thermal, and acoustic—which continuously evaluate the integrity of the manufacturing process. Optical techniques employing high-speed cameras and laser scanners provide real-time, non-contact assessments of the AM process, facilitating the early detection of layer misalignment and surface anomalies. Simultaneously, thermal imaging techniques, such as infrared sensing, play a crucial role in monitoring complex thermal gradients, contributing to defect detection and process control. Acoustic monitoring methods augmented by advancements in audio analysis and machine learning offer cost-effective solutions for discerning the acoustic signatures of AM machinery amidst variable operational conditions. Finally, machine learning is considered an efficient technique for data processing and has shown great promise in feature extraction. Full article

Image processing systems can be used to measure the accuracy of 3D-printed objects. These systems must compare images of the CAD model of the object to be printed with its 3D-printed counterparts to identify any discrepancies. Consequently, the integrity of the accuracy measurement process is heavily dependent on the image processing settings chosen. This study focuses on this issue by developing a customized image processing system. The system generates binary images of a given CAD model and its 3D-printed counterparts and then compares them pixel by pixel to determine the accuracy. Users can experiment with various image processing settings, such as grayscale to binary image conversion threshold, noise reduction parameters, masking parameters, and pixel-fineness adjustment parameters, to see how they affect accuracy. The study concludes that the grayscale to binary image conversion threshold has the most significant impact on accuracy and that the optimal threshold varies depending on the color of the 3D-printed object. The system can also effectively eliminate noise (filament marks) during image processing, ensuring accurate measurements. Additionally, the system can measure the accuracy of highly complex porous structures where the pore size, depth, and distribution are random. The insights gained from this study can be used to develop intelligent systems for the metrology of additive manufacturing. Full article

The formation of brittle intermetallic compounds (IMCs) at the interface between dissimilar materials causes considerable problems. In this study, a multi-material additive manufacturing technique that employs a diode laser and the hot-wire method was developed for stainless steel/aluminum alloys. An Al-Mg aluminum alloy filler wire (JIS 5183-WY) was fed on an austenitic stainless-steel plate (JIS SUS304) while varying the laser power and process speed and using paste-type flux and flux-cored wire. The effects of laser power and process speed on phenomena during manufacturing and IMC formation were investigated. Finally, the wall-type multilayer specimens were fabricated under optimized conditions. The suppression of IMC formation to a thickness of less than 2 μm was achieved in the specimens, along with a high interfacial strength of over 120 MPa on average. Full article

High-feed milling (HFM) represents a progressive manufacturing technology that has recently found widespread application across various industries. HFM is characterized by high machining speed, reduced cycle times, increased overall productivity, and increased tool life. Due to its versatility, HFM is a suitable technology for the application of various materials. The study deals with experimental analysis of cutting forces, machined surface integrity, and statistical evaluation in high-feed machining. In the present study, nickel-copper-based alloy (Monel) was chosen as the machined material, employing HFM with a monolithic ceramic milling cutter. The Monel material is characterized by its excellent mechanical properties and chemical resistance in harsh environments. During machining, cutting forces were recorded in three mutually perpendicular directions. This paper delves into the analysis of the impact of the depth of cut (a_p), width of cut (a_e), and lead-in angle (ε). The chosen evaluation characteristics encompass the tool load, primary profile, and the attained roughness of the machined surface. It is noteworthy that the technology under consideration predominantly aligns with the roughing phase of the manufacturing process. Additionally, the investigation incorporates a statistical analysis of the response surface pertaining to the cutting force components, namely Fx, Fy, Fz, and the resultant cutting force F. Full article

Laser-assisted automated tape placement systems are currently the state of the art regarding thermoplastic tape placement. Flashlamp heating systems are rather new in this field of application and offer high energy density with low safety requirements and moderate costs compared to laser-assisted automated tape placement systems. In this study, the effect of processing parameters on interlaminar bonding of carbon fiber-reinforced polyamide 6 tapes is investigated using a flashlamp heating system. The temperature during placement is monitored using an infrared camera, and the bonding strength is characterized by a wedge peel test. The bonding quality of the tapes placed between 210 °C and 330 °C at a lay-up speed of 50 mm/s is investigated. Thermogravimetric analysis, differential scanning calorimetry, and micrographs are used to investigate the material properties and effects of the processing conditions on the thermophysical properties and geometric properties of the tape. No significant changes in the thermophysical or geometric properties were found. Moisture within the tapes and staining of the quartz guides of the flashlamp system have significant influence on the bonding strength. The highest wedge peel strength of dried tapes was found at around 330 °C. Full article

In this paper, we present an experimental procedure to enhance the dimensional accuracy of fabrication via stereolithography (SLA) of features at the sub-mm scale. Deviations in sub-mm hemispherical cavity diameters were detected and measured on customized samples by confocal microscopy. The characterization and experimental observations of samples allowed the identification of inaccuracy sources, mainly due to the laser beam scanning strategy and the incomplete removal of uncured liquid resin in post-processing (i.e., IPA washing). As a technology baseline, the measured dimensional errors on cavity diameters were up to −46%. A compensation method was defined and implemented, resulting in relevant improvements in dimensional accuracy. However, measurements on sub-mm cavities having different sizes revealed that a constant compensation parameter (i.e., C = 85, 96, 120 μm) is not fully effective at the sub-mm scale, where average errors remain at −24%, −18.8%, and −16% for compensations equal to 85, 96 and 120 μm, respectively. A further experimental campaign allowed the identification of an effective nonlinear compensation law where the compensation parameter depends on the sub-mm feature size C = f(D). Results show a sharp improvement in dimensional accuracy on sub-mm cavity fabrication, with errors consistently below +8.2%. The proposed method can be extended for the fabrication of any sub-mm features without restrictions on the specific technology implementation. Full article

The production of materials with a high affinity for oxidation using the direct metal deposition (DMD) process requires an extended process examination that goes beyond the usual, purely energetic consideration, with the aim of providing sufficient energy to melt the substrate and the powder material supplied. This is because the DMD process does not allow any conclusions to be drawn as to whether it and its respective selected parameters result in an oxidation critical process. To assess this, a superposition of the temperature field with the existing spatial oxygen concentration is required. This work uses this approach to develop an oxidation model that reduces oxidation during the DMD process. In addition to the numerical model, an analytical model is derived, with which the temperature of a material element can be calculated analytically and the resulting boundary oxygen concentration calculated using Fick’s 2nd law. The model also takes into account two-stage oxidation kinetics for Ti alloys. The effect of too high a travel speed (with the same specific energy of the other experiments) is shown visually in the numerical calculation of the temperature field. However, if the process model is taken into account, the components do fulfil the specified requirements. Finally, the effect of oxidation on the microstructure, microhardness, ultimate strength, yield strength and elongation at failure of Ti6Al4V structures produced using DMD is also investigated, and further supports our conclusions regarding the effectiveness of the proposed model. Full article

Joining high strength 2xxx series aluminum is known to be complex and difficult; these alloys are traditionally considered non-weldable for fusion welding. This paper describes details on welding AA2029-T8 for skin-stiffened structures using refill friction stir spot welding (RFSSW). RFSSW is a solid-state process invented in the early 2000s that produces spot welds that are strong, lightweight, flush, and hermetic. Cycle times between 1 and 3 s are discussed, and process forces within a range of 8 to 14 kN are demonstrated. Furthermore, lap-shear quasi-static tensile strengths are shown to be between 10 kN and 12 kN in 9 mm diameter spots. A comparison of the performance of RFSSW welds made with various tool materials—which include H13 tool steel, tungsten carbide, and MP159—is detailed. Comparisons of parameters, weld consolidation, and heat-affected zones are presented with discussion related to heat generation specific to each tool material. Full article

The aim of this paper is to establish a valid procedure for better understanding all of the phenomena associated with the high-speed machining of glass fiber-reinforced plastic (GFRP) composites. Both rectangular and circular specimens were machined at high cutting speeds (up to 50 m/min) in order to understand what occurred for all values of fiber orientation angles during machining operations. An innovative testing methodology was proposed and studied to investigate the phenomenon of burr formation and thus understand how to avoid it during machining operations. To this end, the forces arising during the machining process and the roughness of the resulting surface were carefully studied and correlated with the cutting angle. Additionally, the cutting surface and chip morphology formed during cutting tests were examined using a high-speed camera. Close correlations were found between the variations in the cutting forces’ signals and the trends of the surface roughness and the morphology of the machined surface. Full article

Bio-inspired gyroid triply periodic minimum surface (TPMS) lattice structures have been the focus of research in automotive engineering because they can absorb a lot of energy and have wider plateau ranges. The main challenge is determining the optimal energy absorption capacity and accurately capturing plastic plateau areas using finite element analysis (FEA). Using nTop’s Boolean subtraction method, this study combined walled TPMS gyroid structures with a normal TPMS gyroid lattice. This made a composite TPMS gyroid lattice (CTG) with relative densities ranging from 14% to 54%. Using ideaMaker 4.2.3 (3DRaise Pro 2) software and the fused deposition modeling (FDM) Raise3D Pro 2 3D printer to print polylactic acid (PLA) bioplastics in 1.75 mm filament made it possible to slice computer-aided design (CAD) models and fabricate 36 lattice samples precisely using a layer-by-layer technique. Shimadzu 100 kN testing equipment was utilized for the mechanical compression experiments. The finite element approach validates the results of mechanical compression testing. Further, a composite CTG was examined using a field emission scanning electron microscope (FE-SEM) before and after compression testing. The composite TPMS gyroid lattice showed potential as shock absorbers for vehicles with relative densities of 33%, 38%, and 54%. The Gibson–Ashby model showed that the composite TPMS gyroid lattice deformed mainly by bending, and the size effect was seen when the relative densities were less than 15%. The lattice’s relative density had a significant impact on its ability to absorb energy. The research also explored the use of these innovative foam-like composite TPMS gyroid lattices in high-speed crash box scenarios to potentially enhance vehicle safety and performance. The structures have tremendous potential to improve vehicle safety by acting as advanced shock absorbers, which are particularly effective at higher relative densities. Full article

This article outlines the relevance of building online telemetry systems for online monitoring of the technical conditions of rolling mill equipment. Electromechanical systems of the horizontal stand of the plate Mill 5000 are described, when operating in harsh conditions caused by the shock loading when workpieces enter the stand. It is noted that dynamic torque overloads, exceeding the rated motor torque by many-fold, cause the fatigue failure of spindle joints and breakage of rolls. In this regard, the development and implementation of systems for monitoring the elastic torque on spindles are extremely urgent. This issue has long been studied, but the references provide no information on the building principles and hardware composition of such systems. The use of strain gauges connected according to a balanced bridge circuit to measure the elastic torque is justified. This paper’s contribution is the proposed modular principle for building a telemetry monitoring system based on the analysis of known techniques for measuring and transmitting diagnostic data. The developed system structure is provided and the concept of data transfer and processing are explained. This article suggests the inductive power supply of a measuring unit mounted on a shaft without the use of batteries. A hardware structure was developed to be applied in a system for measuring, transmitting, and visualizing signals proportional to the elastic torque, manufactured on the basis of data measuring instruments by leading companies. The specifics of placement and connection of strain gauges are considered. The hardware providing a wireless power supply to the signal encoder and digital data transfer between the transmitter and receiver is described. The results of implementing the system on Mill 5000 are provided. The installation of a telemetry ring and a receiving head for the inductive power supply and data reception is shown. An experimental assessment of the elastic torques occurring when workpieces enter the cage was obtained by implementing a drive control algorithm which provided biting in the drive acceleration mode. The reliability of measuring the elastic torque with an error not exceeding ±5% and the reduction of dynamic loads on the spindle by 1.3–1.5 times due to the elimination of impacts from closing angular gaps in spindle joints was confirmed. This increases the service life of mechanical equipment and reduces the cost of eliminating the accident aftermath. The prospect of modifying the developed system into a cyber-physical system for monitoring the rolling mill’s mechatronic equipment conditions is shown. Full article